5 ways to design RCM workflows for the biggest impact

These days, we’re all being asked to do more with less. One silver lining? The creative solutions healthcare organizations are deploying to streamline revenue cycle management (RCM) workflows and maximize resources.

We’ll share five tips that can help you improve your first pass payment rate and reduce unnecessary touches in your business office:

• How to categorize account receivable (A/R) tasks for more efficient RCM workflows
• How to calculate the right staffing levels based on claims volume
• How to reduce manual billing and increase insurance follow-up productivity
• Why first pass yield is the most important RCM KPI, and how denial prevention improves it
• Which RCM productivity metrics reveal workflows bottlenecks and performance gaps

What are RCM workflows?

RCM workflows are the processes necessary for a physician or healthcare organization to get paid for the care they provide. RCM workflows include activities like eligibility verification, claim submission, payment capture, and denial management, to name a few.

Effective RCM workflows are an essential ingredient in a healthy balance sheet. Ideally, they should be automated and streamlined as much as possible. This reduces the number of manual touchpoints and shortens the timeline between providing care and collecting the appropriate payment for it.

Designing high-performing RCM workflows

1. Categorize accounts receivable (A/R) tasks

A/R tasks fall into four primary categories: billing, which includes pre-billing activities, claim edits, and attachments; insurance A/R, which includes denials, rejections, and appeals; cash posting, which includes payment posting, reconciliations, and balances/refunds; and self-pay A/R, which includes incoming calls, financial counseling, and bad debt processing.

Categorizing A/R tasks in this manner makes it easier to create more precise workflows, enables more meaningful data analysis, and ensures that staff are able to fully “own” the work within their category.

2. Aligning staffing with claims volume

Do you have the right number of people to manage the workload in each A/R area? Do some simple math to find out.

Let’s say you typically handle 30,000 claims per month. Your goal is for 10% or fewer of those claims to require follow up. This means insurance A/R employees will need to manually follow up on 3,000 claims.

If your productivity standard for insurance A/R is 10 claims per hour, that means it will take 300 hours each month to follow up on the 3,000 claims. 300 hours equates to approximately 2.4 full-time employees.

Of course, the numbers we’ve used in this example are variables. Adjust them as needed based on your actual claims load and KPI targets. Then, repeat this formula for each of the four A/R categories we defined in step 1 to see how your actual headcount compares to the optimal headcount.

3. Optimize staff time across revenue cycle functions

Now that you have an idea of how many staff members you need, it’s time to look at where their time is actually going.

There is no single industry benchmark for how much staff time every organization should devote to billing, insurance A/R, self-pay A/R, or posting. The right mix will vary based on factors such as payer mix, claim volume, technology, and workflow complexity. But the goal is the same: automate repeatable administrative work where possible so staff can focus on the accounts and exceptions that require more attention.

Shift staff time away from:

• Routine claim submission
• Repetitive claim edits
• Manual status checks
• Routine payment posting

Shift staff time toward:

• Insurance A/R follow-up
• Denial resolution and appeals
• Underpayment identification
• Patient balance follow-up
• Complex exceptions and root-cause issues

This shift is especially important because some revenue cycle issues pose significantly greater financial risk than others. In a 2026 MGMA poll, 48% of medical groups identified denials and appeals as their biggest source of revenue cycle leakage, compared with 14% that cited billing and collections and just 2% that cited charge posting.

As RCM workflows become more automated, routine billing activities such as claim scrubbing, submission, status checks, and posting can require less manual effort. That gives staff more capacity to focus on higher-value work that can directly affect reimbursement and A/R performance.

When claim edits do require manual attention, route them to the team closest to the root cause. A deeper look at your claims data can help pinpoint where recurring edits originate, so teams can address the underlying issue instead of repeatedly correcting it downstream.

4. Improve first pass yield through denial management

Insurance follow-up eats up a huge amount of labor. Healthcare organizations can reduce the burden by taking an aggressive approach to denial management and maximizing first pass yield.

First pass yield measures the number of claims paid upon first submission. Focusing on first pass yield as a KPI forces us to also focus on denial prevention, since denials are what prevent claims from getting paid the first time around. Minimizing denials improves first pass yield, which means faster cash flow.

By using technology to analyze denial data, organizations can drill down to the root cause of denials and better focus our mitigation efforts.

5. Measure RCM performance with the right KPIs

There are many ways to analyze your claims data, and each one offers valuable context that can help you continuously improve your RCM workflows.

For example, you can analyze by employee, tracking productivity based on the action taken and comparing different workers against one another. You can analyze by payer, assessing the proportion of denied claims and the reasons for those denials. Both of these views (and others you configure) can inform the design of your RCM workflows.

Additionally, tracking revenue-related metrics like collection rate, resolution rate and appeal success rate will help you make better decisions about where your RCM workflows can be improved.

Reducing not only the number of denials, but the number of touchpoints each denial requires will improve your first pass yield and ultimately put you in a more comfortable financial position.

We take a deeper dive into the analytics mentioned above in our recent post on improving revenue cycle KPIs with analytics.

Want to see the potential positive impact of better workflows for your team? Check out our free RCM ROI calculator.

Frequently Asked Questions on RCM Workflow Design

What does an RCM process flow chart typically look like?

An RCM process flow chart usually starts with patient intake and eligibility verification, moves through billing and claim submission, and continues into insurance follow-up for claims that are denied or rejected. From there it branches into payment posting and reconciliation for claims that are paid, and appeals or resubmission for claims that are not. Self-pay collections typically sit at the end of the chart for balances that remain after insurance has processed a claim. Mapping this out helps identify where in the revenue cycle workflow claims tend to stall, whether that’s a specific payer, a specific denial reason, or a bottleneck in one department’s queue.

What features should RCM tools include for digital health platforms?

Advanced RCM technology reduces manual error through features like batch claim submissions and coverage discovery across primary and secondary payers. On the patient-payment side, updated payment processing technology lets providers accept payments through credit card, check, eCheck, and digital wallets like Apple Pay and Google Pay, and offers automated payment plans for patients who can’t pay their full balance upfront.

How do you optimize a revenue cycle management workflow?

Optimizing a revenue cycle management workflow starts with dividing A/R tasks into clear categories, then checking whether staffing levels in each category match actual claims volume. From there, look at how staff time is actually being spent. Most organizations spend a disproportionate share of time on billing when that work should be mostly automated, freeing up time for insurance A/R and self-pay follow-up. Tracking first pass yield and denial trends over time shows whether those changes are actually improving cash flow.

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